Join our dynamic team as a QA Engineer, focusing on ensuring the quality, performance, and reliability of cutting-edge solutions built on Microsoft Power Platform and Copilot Studio. This role involves rigorous testing of low-code applications, automated workflows, APIs, and conversational AI experiences. You will collaborate closely with developers, data scientists, and business stakeholders to deliver high-quality products.

We are looking for a proactive individual to lead test planning and execution, ensuring seamless integration and exceptional user experience. Your expertise will be crucial in validating data integrations and AI/ML features, making this a pivotal role in our Engineering as a Service/Operate function.

Define and maintain the QA strategy and test approach for Power Platform and Copilot Studio solutions. Create, review, and execute comprehensive test plans and test cases throughout the SDLC. Conduct various testing types including functional, smoke, regression, integration, and end-to-end scenarios. Validate data integrity within Dataverse/Databricks, Power Automate flows, and security configurations. Design and execute conversation test scenarios for chatbots, focusing on context, ambiguity, and error handling. Perform API testing using tools like Postman/JMeter and validate data pipelines involving Azure services. Plan and execute performance and load tests, analyzing results with tools like JMeter. Identify, document, and track defects using Azure DevOps or Jira, and communicate test status and risks effectively.

A Bachelor's degree in a relevant field or equivalent practical experience is required. Possess 4-6 years of experience in Quality Assurance, with at least 1-2 years focused on Microsoft Power Platform. Demonstrated experience testing Power Automate workflows and data-centric applications is essential. Familiarity with Dataverse, Azure Databricks, Azure Storage, and Power Platform connectors is necessary. Working knowledge of chatbot testing methodologies and API testing with Postman/JMeter is expected. Experience with performance testing tools like JMeter and a strong understanding of software testing principles are vital. Ability to validate AI/ML outputs and collaborate with data teams on model behavior is a plus. Familiarity with automation scripting for APIs and regression suites is highly beneficial.